feat(client-sagemaker): Amazon SageMaker Automatic Model Tuning now supports specifying multiple alternate EC2 instance types to make tuning jobs more robust when the preferred instance type is not available due to insufficient capacity.

Author: awstools

clients/client-sagemaker/src/SageMaker.ts

@@ -1291,8 +1291,7 @@ export class SageMaker extends SageMakerClient {
    *             jobs, models, labeling jobs, work teams, endpoint configurations, and
    *             endpoints.</p>
    *         <p>Each tag consists of a key and an optional value. Tag keys must be unique per
-   *             resource. For more information about tags, see For more information, see <a href="https://aws.amazon.com/answers/account-management/aws-tagging-strategies/">Amazon Web Services
-   *                 Tagging Strategies</a>.</p>
+   *             resource. For more information about tags, see For more information, see <a href="https://aws.amazon.com/answers/account-management/aws-tagging-strategies/">Amazon Web Services Tagging Strategies</a>.</p>
    *         <note>
    *             <p>Tags that you add to a hyperparameter tuning job by calling this API are also
    *                 added to any training jobs that the hyperparameter tuning job launches after you
@@ -1435,8 +1434,7 @@ export class SageMaker extends SageMakerClient {
   }
 
   /**
-   * <p>Create a machine learning algorithm that you can use in SageMaker and list in the Amazon Web Services
-   *             Marketplace.</p>
+   * <p>Create a machine learning algorithm that you can use in SageMaker and list in the Amazon Web Services Marketplace.</p>
    */
   public createAlgorithm(
     args: CreateAlgorithmCommandInput,
@@ -1607,8 +1605,8 @@ export class SageMaker extends SageMakerClient {
    *             notebooks you create. The Git repository is a resource in your SageMaker account, so it can
    *             be associated with more than one notebook instance, and it persists independently from
    *             the lifecycle of any notebook instances it is associated with.</p>
-   *         <p>The repository can be hosted either in <a href="https://docs.aws.amazon.com/codecommit/latest/userguide/welcome.html">Amazon Web Services CodeCommit</a> or in any
-   *             other Git repository.</p>
+   *         <p>The repository can be hosted either in <a href="https://docs.aws.amazon.com/codecommit/latest/userguide/welcome.html">Amazon Web Services CodeCommit</a>
+   *             or in any other Git repository.</p>
    */
   public createCodeRepository(
     args: CreateCodeRepositoryCommandInput,
@@ -1988,7 +1986,8 @@ export class SageMaker extends SageMakerClient {
    *                 operations are being performed on the endpoint. To update an endpoint, you must
    *                 create a new <code>EndpointConfig</code>.</p>
    *         </note>
-   *         <p>The endpoint name must be unique within an Amazon Web Services Region in your Amazon Web Services account. </p>
+   *         <p>The endpoint name must be unique within an Amazon Web Services Region in your
+   *                 Amazon Web Services account. </p>
    *         <p>When it receives the request, SageMaker creates the endpoint, launches the resources (ML
    *             compute instances), and deploys the model(s) on them. </p>
    *
@@ -2010,11 +2009,12 @@ export class SageMaker extends SageMakerClient {
    *             check the status of an endpoint, use the <a>DescribeEndpoint</a>
    *             API.</p>
    *         <p>If any of the models hosted at this endpoint get model data from an Amazon S3 location,
-   *             SageMaker uses Amazon Web Services Security Token Service to download model artifacts from the S3 path you
-   *             provided. Amazon Web Services STS is activated in your IAM user account by default. If you previously
-   *             deactivated Amazon Web Services STS for a region, you need to reactivate Amazon Web Services STS for that region. For
-   *             more information, see <a href="https://docs.aws.amazon.com/IAM/latest/UserGuide/id_credentials_temp_enable-regions.html">Activating and
-   *                 Deactivating Amazon Web Services STS in an Amazon Web Services Region</a> in the <i>Amazon Web Services Identity and Access Management User
+   *             SageMaker uses Amazon Web Services Security Token Service to download model artifacts from the
+   *             S3 path you provided. Amazon Web Services STS is activated in your IAM user account by
+   *             default. If you previously deactivated Amazon Web Services STS for a region, you need to
+   *             reactivate Amazon Web Services STS for that region. For more information, see <a href="https://docs.aws.amazon.com/IAM/latest/UserGuide/id_credentials_temp_enable-regions.html">Activating and
+   *                 Deactivating Amazon Web Services STS in an Amazon Web Services Region</a> in the
+   *                     <i>Amazon Web Services Identity and Access Management User
    *                 Guide</i>.</p>
    *         <note>
    *             <p> To add the IAM role policies for using this API operation, go to the <a href="https://console.aws.amazon.com/iam/">IAM console</a>, and choose
@@ -2509,17 +2509,15 @@ export class SageMaker extends SageMakerClient {
    *                 <code>CreateEndpoint</code> API. SageMaker then deploys all of the containers that you
    *             defined for the model in the hosting environment. </p>
    *         <p>For an example that calls this method when deploying a model to SageMaker hosting services,
-   *             see <a href="https://docs.aws.amazon.com/sagemaker/latest/dg/realtime-endpoints-deployment.html#realtime-endpoints-deployment-create-model">Create a Model (Amazon Web Services SDK for Python (Boto
-   *             3)).</a>
+   *             see <a href="https://docs.aws.amazon.com/sagemaker/latest/dg/realtime-endpoints-deployment.html#realtime-endpoints-deployment-create-model">Create a Model (Amazon Web Services SDK for Python (Boto 3)).</a>
    *          </p>
    *         <p>To run a batch transform using your model, you start a job with the
    *                 <code>CreateTransformJob</code> API. SageMaker uses your model and your dataset to get
    *             inferences which are then saved to a specified S3 location.</p>
    *         <p>In the request, you also provide an IAM role that SageMaker can assume to access model
    *             artifacts and docker image for deployment on ML compute hosting instances or for batch
    *             transform jobs. In addition, you also use the IAM role to manage permissions the
-   *             inference code needs. For example, if the inference code access any other Amazon Web Services resources,
-   *             you grant necessary permissions via this role.</p>
+   *             inference code needs. For example, if the inference code access any other Amazon Web Services resources, you grant necessary permissions via this role.</p>
    */
   public createModel(args: CreateModelCommandInput, options?: __HttpHandlerOptions): Promise<CreateModelCommandOutput>;
   public createModel(args: CreateModelCommandInput, cb: (err: any, data?: CreateModelCommandOutput) => void): void;
@@ -2971,7 +2969,7 @@ export class SageMaker extends SageMakerClient {
    *         <note>
    *             <p>The URL that you get from a call to <a>CreatePresignedNotebookInstanceUrl</a> is valid only for 5 minutes. If
    *                 you try to use the URL after the 5-minute limit expires, you are directed to the
-   *                 Amazon Web Services console sign-in page.</p>
+   *                     Amazon Web Services console sign-in page.</p>
    *         </note>
    */
   public createPresignedNotebookInstanceUrl(
@@ -3886,13 +3884,13 @@ export class SageMaker extends SageMakerClient {
    *             endpoint was created. </p>
    *         <p>SageMaker retires any custom KMS key grants associated with the endpoint, meaning you don't
    *             need to use the <a href="http://docs.aws.amazon.com/kms/latest/APIReference/API_RevokeGrant.html">RevokeGrant</a> API call.</p>
-   *         <p>When you delete your endpoint, SageMaker asynchronously deletes associated endpoint resources such as KMS key grants.
-   *             You might still see these resources in your account for a few minutes after deleting your endpoint.
-   *             Do not delete or revoke the permissions for your
-   *             <code>
+   *         <p>When you delete your endpoint, SageMaker asynchronously deletes associated endpoint
+   *             resources such as KMS key grants. You might still see these resources in your account
+   *             for a few minutes after deleting your endpoint. Do not delete or revoke the permissions
+   *             for your <code>
    *                <a href="https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateModel.html#sagemaker-CreateModel-request-ExecutionRoleArn">ExecutionRoleArn</a>
-   *             </code>,
-   *             otherwise SageMaker cannot delete these resources.</p>
+   *             </code>, otherwise SageMaker cannot delete these
+   *             resources.</p>
    */
   public deleteEndpoint(
     args: DeleteEndpointCommandInput,
@@ -4164,9 +4162,9 @@ export class SageMaker extends SageMakerClient {
 
   /**
    * <p>Deletes a model. The <code>DeleteModel</code> API deletes only the model entry that
-   *             was created in SageMaker when you called the <code>CreateModel</code> API. It does not
-   *             delete model artifacts, inference code, or the IAM role that you specified when
-   *             creating the model. </p>
+   *             was created in SageMaker when you called the <code>CreateModel</code> API. It does not delete
+   *             model artifacts, inference code, or the IAM role that you specified when creating the
+   *             model. </p>
    */
   public deleteModel(args: DeleteModelCommandInput, options?: __HttpHandlerOptions): Promise<DeleteModelCommandOutput>;
   public deleteModel(args: DeleteModelCommandInput, cb: (err: any, data?: DeleteModelCommandOutput) => void): void;
@@ -8025,8 +8023,8 @@ export class SageMaker extends SageMakerClient {
   }
 
   /**
-   * <p>Returns a list of the SageMaker notebook instances in the requester's account in an Amazon Web Services
-   *             Region. </p>
+   * <p>Returns a list of the SageMaker notebook instances in the requester's account in an
+   *                 Amazon Web Services Region. </p>
    */
   public listNotebookInstances(
     args: ListNotebookInstancesCommandInput,
@@ -8386,7 +8384,8 @@ export class SageMaker extends SageMakerClient {
    *                     <code>InProgress</code>, are selected (sorted according to the creation time,
    *                 from the most current to the oldest). Next, those with a status of
    *                     <code>InProgress</code> are returned.</p>
-   *             <p>You can quickly test the API using the following Amazon Web Services CLI code.</p>
+   *             <p>You can quickly test the API using the following Amazon Web Services CLI
+   *                 code.</p>
    *             <p>
    *                <code>aws sagemaker list-training-jobs --max-results 100 --status-equals
    *                     InProgress</code>

clients/client-sagemaker/src/commands/AddTagsCommand.ts

@@ -30,8 +30,7 @@ export interface AddTagsCommandOutput extends AddTagsOutput, __MetadataBearer {}
  *             jobs, models, labeling jobs, work teams, endpoint configurations, and
  *             endpoints.</p>
  *         <p>Each tag consists of a key and an optional value. Tag keys must be unique per
- *             resource. For more information about tags, see For more information, see <a href="https://aws.amazon.com/answers/account-management/aws-tagging-strategies/">Amazon Web Services
- *                 Tagging Strategies</a>.</p>
+ *             resource. For more information about tags, see For more information, see <a href="https://aws.amazon.com/answers/account-management/aws-tagging-strategies/">Amazon Web Services Tagging Strategies</a>.</p>
  *         <note>
  *             <p>Tags that you add to a hyperparameter tuning job by calling this API are also
  *                 added to any training jobs that the hyperparameter tuning job launches after you

clients/client-sagemaker/src/commands/CreateAlgorithmCommand.ts

@@ -28,8 +28,7 @@ export interface CreateAlgorithmCommandInput extends CreateAlgorithmInput {}
 export interface CreateAlgorithmCommandOutput extends CreateAlgorithmOutput, __MetadataBearer {}
 
 /**
- * <p>Create a machine learning algorithm that you can use in SageMaker and list in the Amazon Web Services
- *             Marketplace.</p>
+ * <p>Create a machine learning algorithm that you can use in SageMaker and list in the Amazon Web Services Marketplace.</p>
  * @example
  * Use a bare-bones client and the command you need to make an API call.
  * ```javascript

clients/client-sagemaker/src/commands/CreateCodeRepositoryCommand.ts

@@ -33,8 +33,8 @@ export interface CreateCodeRepositoryCommandOutput extends CreateCodeRepositoryO
  *             notebooks you create. The Git repository is a resource in your SageMaker account, so it can
  *             be associated with more than one notebook instance, and it persists independently from
  *             the lifecycle of any notebook instances it is associated with.</p>
- *         <p>The repository can be hosted either in <a href="https://docs.aws.amazon.com/codecommit/latest/userguide/welcome.html">Amazon Web Services CodeCommit</a> or in any
- *             other Git repository.</p>
+ *         <p>The repository can be hosted either in <a href="https://docs.aws.amazon.com/codecommit/latest/userguide/welcome.html">Amazon Web Services CodeCommit</a>
+ *             or in any other Git repository.</p>
  * @example
  * Use a bare-bones client and the command you need to make an API call.
  * ```javascript

clients/client-sagemaker/src/commands/CreateEndpointCommand.ts

@@ -41,7 +41,8 @@ export interface CreateEndpointCommandOutput extends CreateEndpointOutput, __Met
  *                 operations are being performed on the endpoint. To update an endpoint, you must
  *                 create a new <code>EndpointConfig</code>.</p>
  *         </note>
- *         <p>The endpoint name must be unique within an Amazon Web Services Region in your Amazon Web Services account. </p>
+ *         <p>The endpoint name must be unique within an Amazon Web Services Region in your
+ *                 Amazon Web Services account. </p>
  *         <p>When it receives the request, SageMaker creates the endpoint, launches the resources (ML
  *             compute instances), and deploys the model(s) on them. </p>
  *
@@ -63,11 +64,12 @@ export interface CreateEndpointCommandOutput extends CreateEndpointOutput, __Met
  *             check the status of an endpoint, use the <a>DescribeEndpoint</a>
  *             API.</p>
  *         <p>If any of the models hosted at this endpoint get model data from an Amazon S3 location,
- *             SageMaker uses Amazon Web Services Security Token Service to download model artifacts from the S3 path you
- *             provided. Amazon Web Services STS is activated in your IAM user account by default. If you previously
- *             deactivated Amazon Web Services STS for a region, you need to reactivate Amazon Web Services STS for that region. For
- *             more information, see <a href="https://docs.aws.amazon.com/IAM/latest/UserGuide/id_credentials_temp_enable-regions.html">Activating and
- *                 Deactivating Amazon Web Services STS in an Amazon Web Services Region</a> in the <i>Amazon Web Services Identity and Access Management User
+ *             SageMaker uses Amazon Web Services Security Token Service to download model artifacts from the
+ *             S3 path you provided. Amazon Web Services STS is activated in your IAM user account by
+ *             default. If you previously deactivated Amazon Web Services STS for a region, you need to
+ *             reactivate Amazon Web Services STS for that region. For more information, see <a href="https://docs.aws.amazon.com/IAM/latest/UserGuide/id_credentials_temp_enable-regions.html">Activating and
+ *                 Deactivating Amazon Web Services STS in an Amazon Web Services Region</a> in the
+ *                     <i>Amazon Web Services Identity and Access Management User
  *                 Guide</i>.</p>
  *         <note>
  *             <p> To add the IAM role policies for using this API operation, go to the <a href="https://console.aws.amazon.com/iam/">IAM console</a>, and choose

clients/client-sagemaker/src/commands/CreateModelCommand.ts

@@ -39,17 +39,15 @@ export interface CreateModelCommandOutput extends CreateModelOutput, __MetadataB
  *                 <code>CreateEndpoint</code> API. SageMaker then deploys all of the containers that you
  *             defined for the model in the hosting environment. </p>
  *         <p>For an example that calls this method when deploying a model to SageMaker hosting services,
- *             see <a href="https://docs.aws.amazon.com/sagemaker/latest/dg/realtime-endpoints-deployment.html#realtime-endpoints-deployment-create-model">Create a Model (Amazon Web Services SDK for Python (Boto
- *             3)).</a>
+ *             see <a href="https://docs.aws.amazon.com/sagemaker/latest/dg/realtime-endpoints-deployment.html#realtime-endpoints-deployment-create-model">Create a Model (Amazon Web Services SDK for Python (Boto 3)).</a>
  *          </p>
  *         <p>To run a batch transform using your model, you start a job with the
  *                 <code>CreateTransformJob</code> API. SageMaker uses your model and your dataset to get
  *             inferences which are then saved to a specified S3 location.</p>
  *         <p>In the request, you also provide an IAM role that SageMaker can assume to access model
  *             artifacts and docker image for deployment on ML compute hosting instances or for batch
  *             transform jobs. In addition, you also use the IAM role to manage permissions the
- *             inference code needs. For example, if the inference code access any other Amazon Web Services resources,
- *             you grant necessary permissions via this role.</p>
+ *             inference code needs. For example, if the inference code access any other Amazon Web Services resources, you grant necessary permissions via this role.</p>
  * @example
  * Use a bare-bones client and the command you need to make an API call.
  * ```javascript

clients/client-sagemaker/src/commands/CreatePresignedNotebookInstanceUrlCommand.ts

@@ -46,7 +46,7 @@ export interface CreatePresignedNotebookInstanceUrlCommandOutput
  *         <note>
  *             <p>The URL that you get from a call to <a>CreatePresignedNotebookInstanceUrl</a> is valid only for 5 minutes. If
  *                 you try to use the URL after the 5-minute limit expires, you are directed to the
- *                 Amazon Web Services console sign-in page.</p>
+ *                     Amazon Web Services console sign-in page.</p>
  *         </note>
  * @example
  * Use a bare-bones client and the command you need to make an API call.

clients/client-sagemaker/src/commands/DeleteEndpointCommand.ts

@@ -27,13 +27,13 @@ export interface DeleteEndpointCommandOutput extends __MetadataBearer {}
  *             endpoint was created. </p>
  *         <p>SageMaker retires any custom KMS key grants associated with the endpoint, meaning you don't
  *             need to use the <a href="http://docs.aws.amazon.com/kms/latest/APIReference/API_RevokeGrant.html">RevokeGrant</a> API call.</p>
- *         <p>When you delete your endpoint, SageMaker asynchronously deletes associated endpoint resources such as KMS key grants.
- *             You might still see these resources in your account for a few minutes after deleting your endpoint.
- *             Do not delete or revoke the permissions for your
- *             <code>
+ *         <p>When you delete your endpoint, SageMaker asynchronously deletes associated endpoint
+ *             resources such as KMS key grants. You might still see these resources in your account
+ *             for a few minutes after deleting your endpoint. Do not delete or revoke the permissions
+ *             for your <code>
  *                <a href="https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateModel.html#sagemaker-CreateModel-request-ExecutionRoleArn">ExecutionRoleArn</a>
- *             </code>,
- *             otherwise SageMaker cannot delete these resources.</p>
+ *             </code>, otherwise SageMaker cannot delete these
+ *             resources.</p>
  * @example
  * Use a bare-bones client and the command you need to make an API call.
  * ```javascript